Job Description As a Scala Data Engineering Architect at Publicis Sapient, you will lead the design and implementation of modern, cloud-native data platforms that power large-scale digital transformation. This role combines hands-on architecture and team leadership, enabling organizations to unlock the full potential of their data using AWS and Scala-based technologies. Your Impact Architecture & Strategy - Define end-to-end data architecture strategies leveraging AWS and Scala , ensuring scalability, reliability, and alignment with business objectives. - Lead the selection and application of data technologies, frameworks, and patterns tailored to business needs. - Develop and maintain architectural roadmaps for data platform modernization and cloud-native initiatives. Solution Design & Delivery - Translate business requirements into robust, scalable data solutions using AWS-native services and Scala-based frameworks. - Design and implement data ingestion, processing, storage, and analytics pipelines with high availability and performance. - Build reusable components and frameworks to streamline development and accelerate delivery. Technical Leadership - Provide architectural guidance and mentorship to data engineering teams. - Review solution designs to ensure adherence to engineering best practices and standards. - Support project estimation and contribute to delivery plans and technical roadmaps. Client Engagement & Collaboration - Collaborate with business and technical stakeholders to align data strategies with organizational goals. - Facilitate architecture reviews, technical deep dives, and collaborative design sessions. Operational Excellence - Oversee the performance, observability, and automation of data platforms in production environments. - Drive continuous improvements in platform health, data quality, and operational efficiency. Qualifications Your Skills & Experience - Proven experience leading data engineering teams and delivering cloud-native data platforms on AWS . - Strong programming expertise in Scala , particularly for distributed data processing and ETL workflows. - Hands-on experience with AWS services including S3, Glue, EMR, Lambda, Redshift, Athena , and DynamoDB . - Deep understanding of data modeling, data warehousing, and stream/batch data processing frameworks (e.g., Apache Spark ). - Familiarity with infrastructure-as-code and CI/CD for data pipelines (e.g., Terraform, Git, Jenkins ). - Strong communication skills and stakeholder engagement experience in client-facing environments. Set Yourself Apart With - Experience implementing Data Ops and Dev Ops practices in cloud data environments. - Exposure to multi-cloud or hybrid cloud architectures (AWS, GCP, Azure). - Knowledge of observability , logging, and performance optimization strategies for data platforms. #J-18808-Ljbffr